docs: def _adjust_inferential_results_for_parameter_constraints(self,
                                                                constraints):
          """
          Ensure that parameters that were constrained during estimation do not
          have any values showed for inferential results. After all, no inference
          was performed.
  
          Parameters
          ----------
          constraints : list of ints, or None.
              If list, should contain the positions in the array of all estimated
              parameters that were constrained to their initial values.
  
          Returns
          -------
          None.
          """
          if constraints is not None:
              # Ensure the model object has inferential results
              inferential_attributes = ["standard_errors",
                                        "tvalues",
                                        "pvalues",
                                        "robust_std_errs",
                                        "robust_t_stats",
                                        "robust_p_vals"]
              assert all([hasattr(self, x) for x in inferential_attributes])
              assert hasattr(self, "params")
  
              all_names = self.params.index.tolist()
  
              for series in [getattr(self, x) for x in inferential_attributes]:
                  for pos in constraints:
                      series.loc[all_names[pos]] = np.nan
  
          return None